Probability Theory, Statistics, Artificial Intelligence - General, Neural Networks

Advances in Probabilistic Graphical Models

Name: Advances in Probabilistic Graphical Models
Author: Peter Lucas
ISBN: 9783642088544

by Peter Lucas (Editor), Jose A. Gamez (Editor), Antonio Salmeron Cerdan (Editor)

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Overview

This book brings together important topics of current research in probabilistic graphical modeling, learning from data and probabilistic inference. Coverage includes such topics as the characterization of conditional independence, the learning of graphical models with latent variables, and extensions to the influence diagram formalism as well as important application fields, such as the control of vehicles, bioinformatics and medicine.